Translationese

Translators come from various walks of life – former computer programmers, long-time linguists, stay-at-home mothers, former government officials and everything in-between. Because of the diverse skill set required by the translation profession, many translators do not actually ever study translation. They grow-up bilingual or learn languages as a hobby, have a particular aptitude with words, and are familiar with a particular subject matter. In-depth knowledge of a particular genre of text is usually paramount among qualifications. So as much as studying translation is a legitimate pursuit in higher education, it is by no means a prerequisite for becoming a legitimate professional translator. Consequently, many of the long researched questions in translation are not widely known among translators. The findings of the majority of this research are often not influential on the day-to-day work of translation. While it is not a surprise to me that the intellectual pursuits of academia usually do not guide the business world, I do find it lamentable in some cases.

One case in particular is that of translationese. Translationese is the term for the characteristics of language that manifest themselves more abundantly in translated text as opposed to a text generated natively in that language. Researchers have long hypothesized which characteristics or features are unique to translated text, both dependent and independent of source or target languages involved. Here are a few of the features hypothesized: text length, sentence complexity, vocabulary, etc. Essentially translated text is usually more explicit, simpler in vocabulary, and normalized to perceived cultural and language tendencies. Language specific characteristics of translated text vary widely.

There were many early studies on the matter that seemed to validate the hypothesis. Recently, more complex tools and algorithms have been applied to the question and validated it beyond question. Modern tools can classify a text as either translated or original with accuracy greater than 90%.

So how should/could this academic finding influence day-to-day translation? Imagine with me a CAT tool that can identify instances of this “translationese.” One that can show a translator, a project manager, a client, areas of translated text that identify the translation as a translation. Imagine a tool that could suggest a revision that might be less “translationese” and more natural. Sound interesting? I think so.

But there isn’t anything like that…yet. Here at Western Standard, we would like to pursue this technology and include it in Fluency, but we want to know if it would be useful for our users/perspective users. How does it rank on your wish list? The speed with which we undertake this endeavor will be commensurate with the interest expressed, so if you think this would be useful, let us know.

Post navigation

3 thoughts on “Translationese”

I purchased Fluency a couple weeks ago. I've been watching tutorials since then, and would like to state that they are absolutely helpful. Thank you very much for coming up with such a support system.

As for the concept of “translationese”, it would be awesome if a software could recognize a text as a translated text. However, due to the fact that even doing a simple translation task involves countless variables, it seems very difficult to achieve. The biggest obstacle is the method/approach used: foreignizing or domesticating. Should the domestic text (the translation) be read as if it is a native text or should the domestic text be read with its foreign text ( the original text) peculiarities? Only this question brings lots of hot-topics to discuss in terms of language-translation-culture interaction web. I'm doing my research basically on this question in order to advance translation studies one step further.Hopefully, various research findings in the domain will cast new light on the issue.

I find the concept of “translationese” very interesting. Just a few days ago, I came across an article on the French version of slate.com and I immediately sensed a translated text. Although I can't exactly pinpoint what traits betrayed the text as translated, reading the article made me uncomfortable, probably because of the mental energy I had to exert to understand its content.

On a different topic: due to my current trial of Fluency, I think that the use of CAT tools tends to contribute to the “translationese” aspect of a translation. Why? Because we translators also have the correctness of our translation memories lurking in the back of our heads: we (I, for one) don't want to create “bad” translation memories. I've found myself arbitrating between “more natural translation” and “more likely to be reused translation memories”. Clearly, my translation would have been noticeably different if I had gone the plain-text-editor road.

Carl, I would be very interested in reading these academic studies you mentioned. Could you share pointers?